典型二次曲面实时成象的改进算法

在旋转的空间几何模型的Ｐｈｏｎｇ光照模型分析基础上，基于以往的二次曲面等灰度理论，提出了一种新的镜面反射模型和投影等灰度线生成算法，该算法很好地解决了典型二次曲面在三维空间旋转任意角度之后实时地生成Ｐｈｏｎｇ模型光照图象，为二次曲面图元接拼形体奠定了良好的基础。     

基于NSCT变换和PCA的图像融合算法

针对小波变换与Contourlet变换的不足,提出了一种将非下采样Contourlet 变换与主成分分析相结合的图像融合算法。对已配准好的融合源图像作NSCT分解,采用PCA加权融合规则对低频系数处理,采用边缘强度最大的规则对各高频子带系数作融合处理,分别得到融合图像的变换系数,对该系数经NSCT逆变换重构得到融合图像。实验结果表明,算法有效地融合了源图像中的重要信息,融合图像边缘、纹理、细节清晰,得到较好视觉效果和较优的评价指标。     

Evaluation of Characteristics of Non-Metallic Inclusions in P/M Ni-Base Superalloy by Automatic Image Analysis

Non-metallic inclusions,especially the large ones,within P/M Ni-base superalloy have a major influence on fatigue characteristics,but are not directly measurable by routine inspection.In this paper,a method,automatic image analysis,is proposed for estimation of the content,size and amount of non-metallic inclusions in superalloy.The methodology for the practical application of this method is described and the factors affecting the precision of the estimation are discussed.In the experiment,the characteristics of the non-metallic inclusions in Ni-base P/M superalloy are analyzed.     

多分辨率分析及其在图像分解和编码中的应用

多分辨率分析是信号处理特别是图像处理的一种新的有效方法，可以在不同尺度上给出信号的信息。在分析其理论的基础上，将其应用在图像的分析的编码中，最后给出了处理结果。     

土地类型分类的人工神经网络方法

:研究了用人工神经网络对航空影像进行土地类型分类的方法 ,用选定窗口的平均值 ,标准差和傅利叶频谱平均值作为神经网络的输入 ,土地类型的标准值为神经网络的输出。将计算出来的未知土地类型标准值与已知土地类型的标准值相比较 ,可以确定出未知的土地类型。     

Combining Locations from Working Memory and Long-Term Memory into a Common Spatial Image

Abstract

This research uses a novel integration paradigm to investigate whether target locations read in from long-term memory (LTM) differ from perceptually encoded inputs in spatial working-memory (SWM) with respect to systematic spatial error and/or noise, and whether SWM can simultaneously encompass both of these sources. Our results provide evidence for a composite representation of space in SWM derived from both perception and LTM, albeit with a loss in spatial precision of locations retrieved from LTM. More generally, the data support the concept of a spatial image in working memory and extend its potential sources to representations retrieved from LTM.     

Haze removal for UAV reconnaissance images using layered scattering model

During the unmanned aerial vehicles(UAV) reconnaissance missions in the middle-low troposphere, the reconnaissance images are blurred and degraded due to the scattering process of aerosol under fog, haze and other weather conditions, which reduce the image contrast and color fidelity. Considering the characteristics of UAV itself, this paper proposes a new algorithm for dehazing UAV reconnaissance images based on layered scattering model. The algorithm starts with the atmosphere scattering model, using the imaging distance, squint angle and other metadata acquired by the UAV. Based on the original model, a layered scattering model for dehazing is proposed. Considering the relationship between wave-length and extinction coefficient, the airlight intensity and extinction coefficient are calculated in the model. Finally, the restored images are obtained. In addition, a classification method based on Bayesian classification is used for classification of haze concentration of the image, avoiding the trouble of manual working. Then we evaluate the haze removal results according to both the subjective and objective criteria. The experimental results show that compared with the origin image, the comprehensive index of the image restored by our method increases by 282.84%, which proves that our method can obtain excellent dehazing effect.     

卫星转动条件下APS星敏感器星像目标中心提取精度分析

 目前对星敏感器星像定位的研究多限于静态情况,而卫星转动过程中,在曝光期间星像在像平面不断移动,从而影响星像定位的精度,重点分析动态情况下APS星敏感器星像目标中心的提取精度。首先分析采用质心法计算星像目标中心的误差源,提出动态精度的估计方法,并推导相应的计算公式;进而以给定的APS星敏感器参数为基础,研究了计算窗口、曝光时间等精度影响因素的选择方法;最后通过仿真进行了验证。     

基于支持向量机和线性判别分析的维数约减方法及其应用

目前已提出的一些基于支持向量机的维数约减方法,但其投影矩阵的获得仅考虑支持向量机的类间间隔,而忽略了数据中的类内信息。本文首次提出了一种基于支持向量机和线性判别分析的维数约减方法,称之为DRSL。DRSL实现了类问和类内信息的有效组合,能有效拟合数据中类间和类内结构,使得所获投影矩阵能够提高后续分类器的推广能力。实验验证了该方法的有效性。